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Record W1988620011 · doi:10.1149/06105.0097ecst

Structural and Optical Properties of Luminescent Silicon Carbonitride Thin Films

2014· article· en· W1988620011 on OpenAlexafffund
Zahra Khatami, Patrick Robert James Wilson, Owen Taggart, Dan R Frisina, Jacek Wójcik, Peter Mascher

Bibliographic record

VenueECS Transactions · 2014
Typearticle
Languageen
FieldMaterials Science
TopicDiamond and Carbon-based Materials Research
Canadian institutionsMcMaster University
FundersMcMaster University
KeywordsMaterials scienceThin filmPlasma-enhanced chemical vapor depositionPhotoluminescenceAmorphous solidXANESAnalytical Chemistry (journal)Chemical vapor depositionCarbon filmSiliconAmorphous siliconSpectroscopyOptoelectronicsCrystalline siliconNanotechnologyCrystallographyChemistry

Abstract

fetched live from OpenAlex

The composition, structure, and optical characteristics of amorphous hydrogenated silicon carbonitride (a-SiCN:H) thin films were investigated as a function of nitrogen content. The electron cyclotron resonance plasma enhanced chemical vapor deposition (ECR PECVD) technique was utilized to fabricate two different types of a-SiCN:H thin films including films with varying nitrogen contents and films co-doped with cerium and terbium. The intensity and position of the photoluminescence (PL) peak could be tuned in the visible range by controlling the film composition, deposition conditions, and post-deposition thermal treatment. Near edge X-ray absorption fine structure (NEXAFS) spectroscopy at the Si K- and N K-edge were used to perform a comparative structural study on a series of CVD grown a-SiCN:H thin films. A correlation was obtained between the amount of nitrogen in the matrix and the PL behaviour, which also supported the trend in the NEXAFS results.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.382

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.235
Teacher spread0.218 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations3
Published2014
Admission routes2
Has abstractyes

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